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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
datasets:
- stanfordnlp/imdb
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-base-uncased-imdb
results: []
---
# distilbert-base-uncased-imdb
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co./distilbert/distilbert-base-uncased) on the [imdb](https://huggingface.co./datasets/stanfordnlp/imdb) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4367
- Accuracy: 0.9327
- F1: 0.9336
- Precision: 0.9212
- Recall: 0.9463
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2601 | 1.0 | 3125 | 0.3550 | 0.8857 | 0.8744 | 0.9709 | 0.7953 |
| 0.1842 | 2.0 | 6250 | 0.2355 | 0.9327 | 0.9327 | 0.9328 | 0.9326 |
| 0.1191 | 3.0 | 9375 | 0.3287 | 0.9311 | 0.9303 | 0.9417 | 0.9191 |
| 0.0452 | 4.0 | 12500 | 0.4053 | 0.9331 | 0.9337 | 0.9256 | 0.942 |
| 0.0299 | 5.0 | 15625 | 0.4367 | 0.9327 | 0.9336 | 0.9212 | 0.9463 |
### Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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